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Record W2886753541 · doi:10.1109/tcsii.2018.2864700

A 1.5-pJ/bit, 9.04-Mbit/s Carrier-Width Demodulator for Data Transmission Over an Inductive Link Supporting Power and Data Transfer

2018· article· en· W2886753541 on OpenAlexafffund
Aref Trigui, Mohamed Ali, Ahmed Chiheb Ammari, Yvon Savaria, Mohamad Sawan

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2018
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDemodulationData transmissionMegabitTransmission (telecommunications)Computer scienceElectronic engineeringCMOSModulation (music)Bit error rateElectrical engineeringPower (physics)Computer hardwareEngineeringTelecommunicationsChannel (broadcasting)Physics

Abstract

fetched live from OpenAlex

This brief relates to a novel approach for downlink data transmission based on a carrier-width modulation (CWM). This modulation technique offers high performances and allows simultaneous data and power transmission over a single 27.12-MHz inductive link. A CWM demodulator is designed and fabricated in 130-nm CMOS technology. The proposed demodulator is intended for implantable medical devices, but can be applicable to other wireless systems. Excellent measurement results are obtained in comparison with state-of-the-art demodulators used in inductive communication systems. The proposed demodulator that was designed, fabricated, and tested provides high data rates at an ultra-low power budget and a very small silicon area of 2100 μm2. More specifically, a data rate of 9.04 Mb/s can be achieved at a cost of only 13.68 μW power consumption. This represents an energy efficiency of 1.5 pJ/bit, which is 8 times smaller than the best state-of-the-art competitive demodulator.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.288
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2018
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on Circuits & Systems II Express BriefsSame topicWireless Power Transfer SystemsFrench-language works237,207